RESEARCH ARTICLE
Deciphering Transcriptome and Complex Alternative Splicing Transcripts in Mammary Gland Tissues from Cows Naturally Infected with Staphylococcus aureus Mastitis Xiu Ge Wang☯, Zhi Hua Ju☯, Ming Hai Hou☯, Qiang Jiang, Chun Hong Yang, Yan Zhang, Yan Sun, Rong Ling Li, Chang Fa Wang, Ji Feng Zhong, Jin Ming Huang*
a11111
Dairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, Shandong, P.R. China ☯ These authors contributed equally to this work. * [email protected]
Abstract OPEN ACCESS Citation: Wang XG, Ju ZH, Hou MH, Jiang Q, Yang CH, Zhang Y, et al. (2016) Deciphering Transcriptome and Complex Alternative Splicing Transcripts in Mammary Gland Tissues from Cows Naturally Infected with Staphylococcus aureus Mastitis. PLoS ONE 11(7): e0159719. doi:10.1371/journal. pone.0159719 Editor: Marinus F.W. te Pas, Wageningen UR Livestock Research, NETHERLANDS Received: February 22, 2016 Accepted: July 6, 2016 Published: July 26, 2016 Copyright: © 2016 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: Data were deposited in the National Center for Biotechnology Information (NCBI) SRA database (SRX1447227) and within the paper and supporting information.
Alternative splicing (AS) contributes to the complexity of the mammalian proteome and plays an important role in diseases, including infectious diseases. The differential AS patterns of these transcript sequences between the healthy (HS3A) and mastitic (HS8A) cows naturally infected by Staphylococcus aureus were compared to understand the molecular mechanisms underlying mastitis resistance and susceptibility. In this study, using the Illumina paired-end RNA sequencing method, 1352 differentially expressed genes (DEGs) with higher than twofold changes were found in the HS3A and HS8A mammary gland tissues. Gene ontology and KEGG pathway analyses revealed that the cytokine–cytokine receptor interaction pathway is the most significantly enriched pathway. Approximately 16k annotated unigenes were respectively identified in two libraries, based on the bovine Bos taurus UMD3.1 sequence assembly and search. A total of 52.62% and 51.24% annotated unigenes were alternatively spliced in term of exon skipping, intron retention, alternative 50 splicing and alternative 3ʹ splicing. Additionally, 1,317 AS unigenes were HS3A-specific, whereas 1,093 AS unigenes were HS8A-specific. Some immune-related genes, such as ITGB6, MYD88, ADA, ACKR1, and TNFRSF1B, and their potential relationships with mastitis were highlighted. From Chromosome 2, 4, 6, 7, 10, 13, 14, 17, and 20, 3.66% (HS3A) and 5.4% (HS8A) novel transcripts, which harbor known quantitative trait locus associated with clinical mastitis, were identified. Many DEGs in the healthy and mastitic mammary glands are involved in immune, defense, and inflammation responses. These DEGs, which exhibit diverse and specific splicing patterns and events, can endow dairy cattle with the potential complex genetic resistance against mastitis.
Funding: This study was supported by grants from Youth Talents Training Program of Shandong Academy of Agricultural Sciences (SAAS-YTTP2014), the National Natural Science Foundation of China (31371255; 31271328; 31401049), and the Cow Innovation Team of the Shandong Province Modern Agricultural Industry Technology System
PLOS ONE | DOI:10.1371/journal.pone.0159719 July 26, 2016
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(SDAIT-12-011-02). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist.
Introduction Bovine mastitis is an inflammation of the mammary gland invaded and infected by bacteria. This disease results in considerable economic loss and engenders food safety and animal welfare concerns in the dairy industry [1]. The major microorganisms responsible for mastitis are Staphylococcus aureus (Staph. aureus), Streptococcus and Escherichia coli (E. coli). Among these three pathogens, Staph. aureus is the most frequent cause of udder infection [2]. Obtaining insights into the processes of bovine defense and immune response to mastitis could provide new solutions to mastitis infection. Moreover, a genetic strategy based on the molecular mechanism of cow mastitis demonstrates positive effects on the reduction of antibiotic use in dairy cow breeding and improves the safety of milk products [3]. The alternative splicing (AS) of genes is a common phenomenon in mammalian tissues and cell types in response to stimulations in the eukaryon [4–6]. A gene can produce multiple mRNA transcripts and diverse protein isoforms through this process; subsequently, the gene differentiates proteins to display various binding properties, intercellular localizations, and expression regulations, resulting in related, distinct, or even opposing functions [7–9]. Nextgeneration sequencing technology is a rapid and cost-effective approach to screen functional candidate genes, differentially expressed genes (DEGs), and important signal pathways that preliminarily explain the molecular mechanism in various tissues. This technology is also used to further identify gene AS related to important economic traits of interest [10,11]. Recent genome-wide association studies have reported that approximately 27.22% of genes in the bovine embryo [12], 38.85% of genes in the adipose tissue [9], and >90% of genes in human tissues [13] undergo AS. More importantly, splice variants of many immune-related genes are associated with various diseases, such as bovine mastitis [14–16]. These variants are one of the major determinant factors of diseases [17]. Currently knowledge on the molecular mechanism underlying the individual differences in immune response to bovine mastitis, especially at the later stages of natural infection with pathogens, is still limited. The interaction between mastitis pathogens and the host immune system is extremely complex [18]. We hypothesize that the differences induced by the AS of genes can be used by the immune system of cows to process complex information to initiate host response to invading pathogens. Therefore, distinguishing the transcriptomic characteristics and differential patterns of AS in bovine mammary glands between healthy and mastitic cows naturally infected with Staph. aureus is important. To investigate the relevant genes involved in bovine mastitis susceptibility and their regulatory patterns, we initially selected mammary glands from healthy and mastitis-infected cow groups to perform transcriptome sequencing using Illumina HiSeqTM 2000 platform. We obtained a number of candidate genes and signal pathways related to inflammation, defense, and immune responses according to the gene functional annotation and comprehensive analysis of patterns of gene expression. Our findings can provide a foundation for further research on the specific functions of candidate genes related to bovine mastitis susceptibility. The results can also elucidate the molecular process and potential mechanism of cow response to natural infection with Staph. aureus.
Materials and Methods Ethics Statement All experiments were carried out according to the Regulations for the Administration of Affairs Concerning Experimental Animals published by the Ministry of Science and Technology, China in 2004 and approved by the Animal Care and Use Committee from the Dairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Shandong, P. R. China.
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Mammary gland tissues and RNA isolation Six 3- to 5-year-old Holstein cows were obtained from the standardized dairy farm of Shandong Province, China. Three of these cows were healthy, whereas the other three were mastitic cows infected with Staph. aureus. Briefly, a cow was defined as healthy if the clinical symptoms such as swelling, redness, hardness or pain were not observed in the udder and no main pathogens was examined from the cow’s mammary tissues using culture and PCR methods. The mastitis group used for this study was referred to as those cows with Staph. aureus and milk somatic cell count per mL above 1 million. At the slaughterhouse, a part of fresh mammary gland tissue were used for pathogen identification, another samples were cut, cleaned with RNase-free water, and then immediately frozen in liquid nitrogen until further use. After pathological evaluation, the three healthy and three mastitis-infected mammary glands were pooled as HS3A and HS8A groups, respectively. The total RNA from the two pool samples was extracted using Trizol reagent (Invitrogen) according to the manufacturer’s instructions. The quality of RNA samples was assessed with an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). The RNA Integrity Number was 7.6–7.9, and the 28S/18S ratio was 1.9, and the OD260/280 ratio was 2.0.
Construction of cDNA library and sequencing The cDNA libraries of the two groups (HS3A and HS8A) were constructed as follows. First, total RNAs were isolated from the two samples, and the mRNAs were purified and enriched using magnetic beads with oligo (dT). Second, mRNA sequences were fragmented, and firststrand cDNAs were synthesized using the cleaved segments as a template with six base random primers (Illumina). Subsequently, second-strand cDNA synthesis was performed by adding the buffer, dNTPs, RNase H, and DNA polymerase I. Then, the synthesized cDNA was subjected to end-repair and phosphorylation using T4 DNA polymerase, Klenow DNA polymerase and T4 PNK. Third, Poly (A) and sequencing joints were added to the cDNA. Fourth, the products of ligation reaction were purified on a 2% TAE-agarose gel. A range of cDNA fragments (200 ± 25 bp) were selected from the agarose gel. Fifteen rounds of PCR amplification were performed to enrich the cDNA template using PCR Primer PE 1.0 and PE 2.0 (Illumina) with Phusion DNA Polymerase. Finally, the two constructed libraries were sequenced using the PE technology (2 × 75 bp read length) Illumina HiSeqTM 2000 platform (BGI, Shenzhen, China). The randomness of mRNA fragmentation was evaluated with the distribution of reads in the reference genes (Fig A in S1 File).
Data filtering and transcriptome assembly Raw reads were cleaned by removing adapter sequences as well as reads with too many unknown base calls (N), low complexity, and low-quality bases, and data quality was controlled by a stringent process to improve the accuracy of the transcriptome analysis results. Reads were filtered following three criteria. (1) Reads with adapter contaminant were first removed. (2) Reads in which the percentage of unknown nucleotides was higher than 5%, the corresponding reads were discarded. (3) Reads in which the percentage of bases with a quality score of 5 was greater than 50% were eliminated. After clean data from the HS3A and HS8A were generated, transcriptome assemblies were performed using the SOAP2 software [19]. The genome assembly Bos taurus UMD3.1 deposited in Ensembl (http://www.ensembl.org/info/ data/ftp/index.html) was used as the reference genome. We gathered the paired-end (PE) reads with one end mapped on the unique contig and the other end located in the gap region to further shorten the remaining gaps. We also performed local assembly with the unmapped end to
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fill in the small gaps within the scaffolds. Such sequences that contain the least “N” and do not extend on either end were defined as unigenes.
Identification of differentially expressed genes The expression levels of genes were calculated using the RPKM method to identify the DEGs between the healthy HS3A and mastitic HS8A groups. This method can eliminate the influence of deviations in transcript lengths and sequencing levels [20]. The corresponding formula is RPKM = (106C)/(NL/103), where C is the number of fragments aligned to the exons of the gene, N is the number of total fragments aligned to all the genes, and L is the base number of the gene CDS. In our analysis, the DEGs were screened using a false discovery rate threshold value of 0.001 and an absolute value of log2 ratio of 1. All fold changes of differentially expressed genes are log2 values.
Enrichment analysis of differentially expressed genes The potential functions of assembled DEGs were predicted and annotated against the Gene ontology (GO) and KEGG protein databases. The GO terms especially enriched in DEGs were defined using hypergeometric distribution testing and Bonferroni correction with p-value 0.05 as the threshold. For the KEGG protein database, detailed information about each gene can be shown in a signal pathway to reveal its molecular regulatory network and metabolic pathway. The enrichment of a pathway is obtained by multiple testing and is considered significant if q-value 0.05.
Alternative splicing analysis of genes We used SOAPsplice software with a default setting and RNA-Seq data to detect splice junctions and identify the potential AS patterns of genes (Fig B in S1 File). SOAPsplice uses a novel approach comprising the following steps: (1) identifying as many reasonable splice junction candidates as possible and (2) filtering the false positives with two effective filtering strategies [21]. First, junction sites, which provide information about boundaries and combinations of different exons in a transcript, are detected by SOAPsplice. Then, all junction sites of the same gene are used to distinguish the type of AS event. A brief introduction of the algorithms used to detect the four AS events in this study is provided in Fig C in S1 File.
Prediction of novel transcripts Transcripts with reads were assembled using Cufflink [22]. Reads that are continuous and overlapping according to the distribution of reads on the reference genome would form a transcriptional activity area (TAR). Different TARs were linked to form an assembled transcript (Fig D in S1 File). If the gene models were found in intergenic regions (200 bp away from upstream or downstream genes), the transcripts were regarded as candidates for novel transcripts.
Results Illumina paired-end sequencing and transcriptome assembly RNA was extracted from the healthy and Staph. aureus-infected mammary tissues to generate a comprehensive survey of genes associated with mastitis infection. Each sequencing feature obtained using Illumina PE sequencing technology yielded 2 × 75 bp independent reads from either end of a cDNA fragment. In the present study, a total of 80% and 78.65% sequencing reads in the HS3A and HS8A were mapped onto the reference Bos taurus genome assembly
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Table 1. Sequencing and assembly results of two libraries. Healthy group (H3A)
Mastitic group (H8A)
Total number of reads
53333334
49245176
Total mapped reads
42664111
38733278
Percentage (%) of mapped reads to genome
80.00
78.65
Total unigenes
16247
16246
Minimun length (bp) of unigene
147
147
Maximun length (bp) of unigene
22023
22023
Average length (bp) of unigene
2165
2168
doi:10.1371/journal.pone.0159719.t001
(UMD3.1), respectively. Finally, the read assembly yielded approximate 16k unigenes with an average length of 2k bp in two libraries (Table 1). Determining subtle transcriptomic changes in the alveolar mammary tissues can provide insights into molecular mechanisms underlying biological processes, such as immune and defense responses against mastitic infection. In this study, 1,352 DEGs were identified, including 602 up-regulated genes and 750 down-regulated genes, and found specific to the HS8A mammary gland tissue (Table A in S2 File). The top 100 DEGs from the aforementioned genes were selected by the reads per kilobase of the exon model per million mapped reads (RPKM) calculation and further ranked based on the expression fold change value [log2(HS8A/HS3A)] of the genes (Table B in S2 File). Out of the 100 top DEGs, 66% (66/100) genes were up-regulated in the HS8A, indicating that these genes play important roles bovine response to mastitis. A total of 1,352 DEGs were matched and classified into three functional categories, namely, molecular function (MF), biological process (BP), and cellular component (CC), according to the GO classification system. Among these DEGs, 1,028 matched genes were involved in molecular functions and were clustered into 367 classifications. The top 10 significant enrichment GO terms, such as the protein binding, cytokine activity, receptor binding, chemokine receptor activity, and chemokine binding were also significantly enriched (Table A in S3 File). For the BP, the “response to stimulus” term (32.5%, 332 out of 1,023 DEGs) was the most significant enrichment (Table B in S3 File). Moreover, 124, 74, 17, and 55 DEGs were significantly enriched (p < 0.05) and respectively classified into the GO terms immune system process, defense response, regulation of cell migration, and regulation of immune system process. In addition, 38, 30, 28, 22, 69, and 6 DEGs were respectively classified into the GO terms response to wounding, immune response, response to bacterium, inflammatory response, programmed cell death, and innate immune response in spite of their non-significant enrichments (p > 0.05, Table B in S3 File). The 60 DEGs participating in the “immune system process,” “defense response,” “immune response,” and “inflammatory response” GO terms and expressing with above 1.5-fold change in two groups are listed in S4 File. For the CC analysis, “extracellular region” was the most abundant GO term (Table C in S3 File). To further understand the biological functions of the unigenes, we mapped DEGs to the signal pathways described in KEGG. Consequently, 1,349 genes were assigned to the KEGG database, and these genes were classified into 221 biological pathways based on the reference canonical pathways. Thirty-three highly ranked KEGG pathway were significantly enriched (p T in the alpha-2macroglobulin gene causing aberrant splice variants is associated with mastitis in dairy cattle. Immunogenetics 64: 807–816. doi: 10.1007/s00251-012-0639-8 PMID: 22923050
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Deciphering Transcriptome and Complex Alternative Splicing Transcripts in Mammary Gland Tissues from Cows Naturally Infected with Staphylococcus aureus Mastitis Xiu Ge Wang☯, Zhi Hua Ju☯, Ming Hai Hou☯, Qiang Jiang, Chun Hong Yang, Yan Zhang, Yan Sun, Rong Ling Li, Chang Fa Wang, Ji Feng Zhong, Jin Ming Huang*
a11111
Dairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, Shandong, P.R. China ☯ These authors contributed equally to this work. * [email protected]
Abstract OPEN ACCESS Citation: Wang XG, Ju ZH, Hou MH, Jiang Q, Yang CH, Zhang Y, et al. (2016) Deciphering Transcriptome and Complex Alternative Splicing Transcripts in Mammary Gland Tissues from Cows Naturally Infected with Staphylococcus aureus Mastitis. PLoS ONE 11(7): e0159719. doi:10.1371/journal. pone.0159719 Editor: Marinus F.W. te Pas, Wageningen UR Livestock Research, NETHERLANDS Received: February 22, 2016 Accepted: July 6, 2016 Published: July 26, 2016 Copyright: © 2016 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: Data were deposited in the National Center for Biotechnology Information (NCBI) SRA database (SRX1447227) and within the paper and supporting information.
Alternative splicing (AS) contributes to the complexity of the mammalian proteome and plays an important role in diseases, including infectious diseases. The differential AS patterns of these transcript sequences between the healthy (HS3A) and mastitic (HS8A) cows naturally infected by Staphylococcus aureus were compared to understand the molecular mechanisms underlying mastitis resistance and susceptibility. In this study, using the Illumina paired-end RNA sequencing method, 1352 differentially expressed genes (DEGs) with higher than twofold changes were found in the HS3A and HS8A mammary gland tissues. Gene ontology and KEGG pathway analyses revealed that the cytokine–cytokine receptor interaction pathway is the most significantly enriched pathway. Approximately 16k annotated unigenes were respectively identified in two libraries, based on the bovine Bos taurus UMD3.1 sequence assembly and search. A total of 52.62% and 51.24% annotated unigenes were alternatively spliced in term of exon skipping, intron retention, alternative 50 splicing and alternative 3ʹ splicing. Additionally, 1,317 AS unigenes were HS3A-specific, whereas 1,093 AS unigenes were HS8A-specific. Some immune-related genes, such as ITGB6, MYD88, ADA, ACKR1, and TNFRSF1B, and their potential relationships with mastitis were highlighted. From Chromosome 2, 4, 6, 7, 10, 13, 14, 17, and 20, 3.66% (HS3A) and 5.4% (HS8A) novel transcripts, which harbor known quantitative trait locus associated with clinical mastitis, were identified. Many DEGs in the healthy and mastitic mammary glands are involved in immune, defense, and inflammation responses. These DEGs, which exhibit diverse and specific splicing patterns and events, can endow dairy cattle with the potential complex genetic resistance against mastitis.
Funding: This study was supported by grants from Youth Talents Training Program of Shandong Academy of Agricultural Sciences (SAAS-YTTP2014), the National Natural Science Foundation of China (31371255; 31271328; 31401049), and the Cow Innovation Team of the Shandong Province Modern Agricultural Industry Technology System
PLOS ONE | DOI:10.1371/journal.pone.0159719 July 26, 2016
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Bovine Transcriptome and Alternative Splicing
(SDAIT-12-011-02). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist.
Introduction Bovine mastitis is an inflammation of the mammary gland invaded and infected by bacteria. This disease results in considerable economic loss and engenders food safety and animal welfare concerns in the dairy industry [1]. The major microorganisms responsible for mastitis are Staphylococcus aureus (Staph. aureus), Streptococcus and Escherichia coli (E. coli). Among these three pathogens, Staph. aureus is the most frequent cause of udder infection [2]. Obtaining insights into the processes of bovine defense and immune response to mastitis could provide new solutions to mastitis infection. Moreover, a genetic strategy based on the molecular mechanism of cow mastitis demonstrates positive effects on the reduction of antibiotic use in dairy cow breeding and improves the safety of milk products [3]. The alternative splicing (AS) of genes is a common phenomenon in mammalian tissues and cell types in response to stimulations in the eukaryon [4–6]. A gene can produce multiple mRNA transcripts and diverse protein isoforms through this process; subsequently, the gene differentiates proteins to display various binding properties, intercellular localizations, and expression regulations, resulting in related, distinct, or even opposing functions [7–9]. Nextgeneration sequencing technology is a rapid and cost-effective approach to screen functional candidate genes, differentially expressed genes (DEGs), and important signal pathways that preliminarily explain the molecular mechanism in various tissues. This technology is also used to further identify gene AS related to important economic traits of interest [10,11]. Recent genome-wide association studies have reported that approximately 27.22% of genes in the bovine embryo [12], 38.85% of genes in the adipose tissue [9], and >90% of genes in human tissues [13] undergo AS. More importantly, splice variants of many immune-related genes are associated with various diseases, such as bovine mastitis [14–16]. These variants are one of the major determinant factors of diseases [17]. Currently knowledge on the molecular mechanism underlying the individual differences in immune response to bovine mastitis, especially at the later stages of natural infection with pathogens, is still limited. The interaction between mastitis pathogens and the host immune system is extremely complex [18]. We hypothesize that the differences induced by the AS of genes can be used by the immune system of cows to process complex information to initiate host response to invading pathogens. Therefore, distinguishing the transcriptomic characteristics and differential patterns of AS in bovine mammary glands between healthy and mastitic cows naturally infected with Staph. aureus is important. To investigate the relevant genes involved in bovine mastitis susceptibility and their regulatory patterns, we initially selected mammary glands from healthy and mastitis-infected cow groups to perform transcriptome sequencing using Illumina HiSeqTM 2000 platform. We obtained a number of candidate genes and signal pathways related to inflammation, defense, and immune responses according to the gene functional annotation and comprehensive analysis of patterns of gene expression. Our findings can provide a foundation for further research on the specific functions of candidate genes related to bovine mastitis susceptibility. The results can also elucidate the molecular process and potential mechanism of cow response to natural infection with Staph. aureus.
Materials and Methods Ethics Statement All experiments were carried out according to the Regulations for the Administration of Affairs Concerning Experimental Animals published by the Ministry of Science and Technology, China in 2004 and approved by the Animal Care and Use Committee from the Dairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Shandong, P. R. China.
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Mammary gland tissues and RNA isolation Six 3- to 5-year-old Holstein cows were obtained from the standardized dairy farm of Shandong Province, China. Three of these cows were healthy, whereas the other three were mastitic cows infected with Staph. aureus. Briefly, a cow was defined as healthy if the clinical symptoms such as swelling, redness, hardness or pain were not observed in the udder and no main pathogens was examined from the cow’s mammary tissues using culture and PCR methods. The mastitis group used for this study was referred to as those cows with Staph. aureus and milk somatic cell count per mL above 1 million. At the slaughterhouse, a part of fresh mammary gland tissue were used for pathogen identification, another samples were cut, cleaned with RNase-free water, and then immediately frozen in liquid nitrogen until further use. After pathological evaluation, the three healthy and three mastitis-infected mammary glands were pooled as HS3A and HS8A groups, respectively. The total RNA from the two pool samples was extracted using Trizol reagent (Invitrogen) according to the manufacturer’s instructions. The quality of RNA samples was assessed with an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). The RNA Integrity Number was 7.6–7.9, and the 28S/18S ratio was 1.9, and the OD260/280 ratio was 2.0.
Construction of cDNA library and sequencing The cDNA libraries of the two groups (HS3A and HS8A) were constructed as follows. First, total RNAs were isolated from the two samples, and the mRNAs were purified and enriched using magnetic beads with oligo (dT). Second, mRNA sequences were fragmented, and firststrand cDNAs were synthesized using the cleaved segments as a template with six base random primers (Illumina). Subsequently, second-strand cDNA synthesis was performed by adding the buffer, dNTPs, RNase H, and DNA polymerase I. Then, the synthesized cDNA was subjected to end-repair and phosphorylation using T4 DNA polymerase, Klenow DNA polymerase and T4 PNK. Third, Poly (A) and sequencing joints were added to the cDNA. Fourth, the products of ligation reaction were purified on a 2% TAE-agarose gel. A range of cDNA fragments (200 ± 25 bp) were selected from the agarose gel. Fifteen rounds of PCR amplification were performed to enrich the cDNA template using PCR Primer PE 1.0 and PE 2.0 (Illumina) with Phusion DNA Polymerase. Finally, the two constructed libraries were sequenced using the PE technology (2 × 75 bp read length) Illumina HiSeqTM 2000 platform (BGI, Shenzhen, China). The randomness of mRNA fragmentation was evaluated with the distribution of reads in the reference genes (Fig A in S1 File).
Data filtering and transcriptome assembly Raw reads were cleaned by removing adapter sequences as well as reads with too many unknown base calls (N), low complexity, and low-quality bases, and data quality was controlled by a stringent process to improve the accuracy of the transcriptome analysis results. Reads were filtered following three criteria. (1) Reads with adapter contaminant were first removed. (2) Reads in which the percentage of unknown nucleotides was higher than 5%, the corresponding reads were discarded. (3) Reads in which the percentage of bases with a quality score of 5 was greater than 50% were eliminated. After clean data from the HS3A and HS8A were generated, transcriptome assemblies were performed using the SOAP2 software [19]. The genome assembly Bos taurus UMD3.1 deposited in Ensembl (http://www.ensembl.org/info/ data/ftp/index.html) was used as the reference genome. We gathered the paired-end (PE) reads with one end mapped on the unique contig and the other end located in the gap region to further shorten the remaining gaps. We also performed local assembly with the unmapped end to
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Bovine Transcriptome and Alternative Splicing
fill in the small gaps within the scaffolds. Such sequences that contain the least “N” and do not extend on either end were defined as unigenes.
Identification of differentially expressed genes The expression levels of genes were calculated using the RPKM method to identify the DEGs between the healthy HS3A and mastitic HS8A groups. This method can eliminate the influence of deviations in transcript lengths and sequencing levels [20]. The corresponding formula is RPKM = (106C)/(NL/103), where C is the number of fragments aligned to the exons of the gene, N is the number of total fragments aligned to all the genes, and L is the base number of the gene CDS. In our analysis, the DEGs were screened using a false discovery rate threshold value of 0.001 and an absolute value of log2 ratio of 1. All fold changes of differentially expressed genes are log2 values.
Enrichment analysis of differentially expressed genes The potential functions of assembled DEGs were predicted and annotated against the Gene ontology (GO) and KEGG protein databases. The GO terms especially enriched in DEGs were defined using hypergeometric distribution testing and Bonferroni correction with p-value 0.05 as the threshold. For the KEGG protein database, detailed information about each gene can be shown in a signal pathway to reveal its molecular regulatory network and metabolic pathway. The enrichment of a pathway is obtained by multiple testing and is considered significant if q-value 0.05.
Alternative splicing analysis of genes We used SOAPsplice software with a default setting and RNA-Seq data to detect splice junctions and identify the potential AS patterns of genes (Fig B in S1 File). SOAPsplice uses a novel approach comprising the following steps: (1) identifying as many reasonable splice junction candidates as possible and (2) filtering the false positives with two effective filtering strategies [21]. First, junction sites, which provide information about boundaries and combinations of different exons in a transcript, are detected by SOAPsplice. Then, all junction sites of the same gene are used to distinguish the type of AS event. A brief introduction of the algorithms used to detect the four AS events in this study is provided in Fig C in S1 File.
Prediction of novel transcripts Transcripts with reads were assembled using Cufflink [22]. Reads that are continuous and overlapping according to the distribution of reads on the reference genome would form a transcriptional activity area (TAR). Different TARs were linked to form an assembled transcript (Fig D in S1 File). If the gene models were found in intergenic regions (200 bp away from upstream or downstream genes), the transcripts were regarded as candidates for novel transcripts.
Results Illumina paired-end sequencing and transcriptome assembly RNA was extracted from the healthy and Staph. aureus-infected mammary tissues to generate a comprehensive survey of genes associated with mastitis infection. Each sequencing feature obtained using Illumina PE sequencing technology yielded 2 × 75 bp independent reads from either end of a cDNA fragment. In the present study, a total of 80% and 78.65% sequencing reads in the HS3A and HS8A were mapped onto the reference Bos taurus genome assembly
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Table 1. Sequencing and assembly results of two libraries. Healthy group (H3A)
Mastitic group (H8A)
Total number of reads
53333334
49245176
Total mapped reads
42664111
38733278
Percentage (%) of mapped reads to genome
80.00
78.65
Total unigenes
16247
16246
Minimun length (bp) of unigene
147
147
Maximun length (bp) of unigene
22023
22023
Average length (bp) of unigene
2165
2168
doi:10.1371/journal.pone.0159719.t001
(UMD3.1), respectively. Finally, the read assembly yielded approximate 16k unigenes with an average length of 2k bp in two libraries (Table 1). Determining subtle transcriptomic changes in the alveolar mammary tissues can provide insights into molecular mechanisms underlying biological processes, such as immune and defense responses against mastitic infection. In this study, 1,352 DEGs were identified, including 602 up-regulated genes and 750 down-regulated genes, and found specific to the HS8A mammary gland tissue (Table A in S2 File). The top 100 DEGs from the aforementioned genes were selected by the reads per kilobase of the exon model per million mapped reads (RPKM) calculation and further ranked based on the expression fold change value [log2(HS8A/HS3A)] of the genes (Table B in S2 File). Out of the 100 top DEGs, 66% (66/100) genes were up-regulated in the HS8A, indicating that these genes play important roles bovine response to mastitis. A total of 1,352 DEGs were matched and classified into three functional categories, namely, molecular function (MF), biological process (BP), and cellular component (CC), according to the GO classification system. Among these DEGs, 1,028 matched genes were involved in molecular functions and were clustered into 367 classifications. The top 10 significant enrichment GO terms, such as the protein binding, cytokine activity, receptor binding, chemokine receptor activity, and chemokine binding were also significantly enriched (Table A in S3 File). For the BP, the “response to stimulus” term (32.5%, 332 out of 1,023 DEGs) was the most significant enrichment (Table B in S3 File). Moreover, 124, 74, 17, and 55 DEGs were significantly enriched (p < 0.05) and respectively classified into the GO terms immune system process, defense response, regulation of cell migration, and regulation of immune system process. In addition, 38, 30, 28, 22, 69, and 6 DEGs were respectively classified into the GO terms response to wounding, immune response, response to bacterium, inflammatory response, programmed cell death, and innate immune response in spite of their non-significant enrichments (p > 0.05, Table B in S3 File). The 60 DEGs participating in the “immune system process,” “defense response,” “immune response,” and “inflammatory response” GO terms and expressing with above 1.5-fold change in two groups are listed in S4 File. For the CC analysis, “extracellular region” was the most abundant GO term (Table C in S3 File). To further understand the biological functions of the unigenes, we mapped DEGs to the signal pathways described in KEGG. Consequently, 1,349 genes were assigned to the KEGG database, and these genes were classified into 221 biological pathways based on the reference canonical pathways. Thirty-three highly ranked KEGG pathway were significantly enriched (p T in the alpha-2macroglobulin gene causing aberrant splice variants is associated with mastitis in dairy cattle. Immunogenetics 64: 807–816. doi: 10.1007/s00251-012-0639-8 PMID: 22923050
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